| 2026 | AAAI | Tractable Weighted First-Order Model Counting with Bounded Treewidth Binary Evidence. | Vclav Kula, Qipeng Kuang, Yuyi Wang, Yuanhong Wang, Ondrej Kuzelka |
| 2026 | CSL | Bridging Weighted First Order Model Counting and Graph Polynomials. | Qipeng Kuang, Ondrej Kuzelka, Yuanhong Wang, Yuyi Wang |
| 2026 | SAT | On Knowledge Compilation for Two-Variable First-Order Logic. | Qiaolan Meng, Juhua Pu, Hongting Niu, Yuyi Wang, Yuanhong Wang, Ondrej Kuzelka |
| 2025 | ECAI | Faster Lifting for Ordered Domains with Predecessor Relations. | Kuncheng Zou, Jiahao Mai, Yonggang Zhang, Yuyi Wang, Ondrej Kuzelka, Yuanhong Wang, Yi Chang |
| 2025 | LICS | Model Enumeration of Two-Variable Logic with Quadratic Delay Complexity. | Qiaolan Meng, Juhua Pu, Hongting Niu, Yuyi Wang, Yuanhong Wang, Ondrej Kuzelka |
| 2024 | ECAI | A More Practical Algorithm for Weighted First-Order Model Counting with Linear Order Axiom. | Qiaolan Meng, Jan Tth, Yuanhong Wang, Yuyi Wang, Ondrej Kuzelka |
| 2024 | KR | Complexity of Weighted First-Order Model Counting in the Two-Variable Fragment with Counting Quantifiers: A Bound to Beat. | Jan Tth, Ondrej Kuzelka |
| 2023 | AAAI | Lifted Inference with Linear Order Axiom. | Jan Tth, Ondrej Kuzelka |
| 2023 | IJCAI | Counting and Sampling Models in First-Order Logic. | Ondrej Kuzelka |
| 2023 | IJCAI | On Discovering Interesting Combinatorial Integer Sequences. | Martin Svatos, Peter Jung, Jan Tth, Yuyi Wang, Ondrej Kuzelka |
| 2023 | LICS | On Exact Sampling in the Two-Variable Fragment of First-Order Logic. | Yuanhong Wang, Juhua Pu, Yuyi Wang, Ondrej Kuzelka |
| 2022 | AAAI | Domain-Lifted Sampling for Universal Two-Variable Logic and Extensions. | Yuanhong Wang, Timothy van Bremen, Yuyi Wang, Ondrej Kuzelka |
| 2021 | AISTATS | Context-Specific Likelihood Weighting. | Nitesh Kumar, Ondrej Kuzelka |
| 2021 | ICLR | Lossless Compression of Structured Convolutional Models via Lifting. | Gustav Sourek, Filip Zelezn, Ondrej Kuzelka |
| 2021 | IJCAI | Fast Algorithms for Relational Marginal Polytopes. | Yuanhong Wang, Timothy van Bremen, Juhua Pu, Yuyi Wang, Ondrej Kuzelka |
| 2021 | ILP | Automatic Conjecturing of P-Recursions Using Lifted Inference. | Jchym Barvnek, Timothy van Bremen, Yuyi Wang, Filip Zelezn, Ondrej Kuzelka |
| 2021 | KR | Lifted Inference with Tree Axioms. | Timothy van Bremen, Ondrej Kuzelka |
| 2021 | UAI | Faster lifting for two-variable logic using cell graphs. | Timothy van Bremen, Ondrej Kuzelka |
| 2021 | UAI | Neural markov logic networks. | Giuseppe Marra, Ondrej Kuzelka |
| 2020 | AISTATS | Domain-Liftability of Relational Marginal Polytopes. | Ondrej Kuzelka, Yuyi Wang |
| 2020 | ECAI | STRiKE: Rule-Driven Relational Learning Using Stratified k-Entailment. | Martin Svatos, Steven Schockaert, Jesse Davis, Ondrej Kuzelka |
| 2020 | IJCAI | Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry. | Timothy van Bremen, Ondrej Kuzelka |
| 2020 | UAI | Complex Markov Logic Networks: Expressivity and Liftability. | Ondrej Kuzelka |
| 2019 | AISTATS | Lifted Weight Learning of Markov Logic Networks Revisited. | Ondrej Kuzelka, Vyacheslav Kungurtsev |
| 2019 | NeSy | Scaling up relational templated neural models. | Gustav Sourek, Filip Zelezn, Ondrej Kuzelka |
| 2019 | UAI | Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption. | Ondrej Kuzelka, Jesse Davis |
| 2018 | AAAI | Relational Marginal Problems: Theory and Estimation. | Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert |
| 2018 | CoNLL | Modelling Salient Features as Directions in Fine-Tuned Semantic Spaces. | Thomas Ager, Ondrej Kuzelka, Steven Schockaert |
| 2018 | KR | Quantified Markov Logic Networks. | Vctor Gutirrez-Basulto, Jean Christoph Jung, Ondrej Kuzelka |
| 2018 | UAI | PAC-Reasoning in Relational Domains. | Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert |
| 2017 | IJCAI | Induction of Interpretable Possibilistic Logic Theories from Relational Data. | Ondrej Kuzelka, Jesse Davis, Steven Schockaert |
| 2017 | ILP | Stacked Structure Learning for Lifted Relational Neural Networks. | Gustav Sourek, Martin Svatos, Filip Zelezn, Steven Schockaert, Ondrej Kuzelka |
| 2017 | ILP | Pruning Hypothesis Spaces Using Learned Domain Theories. | Martin Svatos, Gustav Sourek, Filip Zelezn, Steven Schockaert, Ondrej Kuzelka |
| 2016 | ECAI | Interpretable Encoding of Densities Using Possibilistic Logic. | Ondrej Kuzelka, Jesse Davis, Steven Schockaert |
| 2016 | IJCAI | Learning Possibilistic Logic Theories from Default Rules. | Ondrej Kuzelka, Jesse Davis, Steven Schockaert |
| 2016 | IJCAI | Bounds for Learning from Evolutionary-Related Data in the Realizable Case. | Ondrej Kuzelka, Yuyi Wang, Jan Ramon |
| 2016 | ILP | Learning Predictive Categories Using Lifted Relational Neural Networks. | Gustav Sourek, Suresh Manandhar, Filip Zelezn, Steven Schockaert, Ondrej Kuzelka |
| 2016 | NeSy | Inducing Symbolic Rules from Entity Embeddings using Auto-encoders. | Thomas Ager, Ondrej Kuzelka, Steven Schockaert |
| 2015 | ILP | Constructing Markov Logic Networks from First-Order Default Rules. | Ondrej Kuzelka, Jesse Davis, Steven Schockaert |
| 2015 | ILP | Mine 'Em All: A Note on Mining All Graphs. | Ondrej Kuzelka, Jan Ramon |
| 2015 | ILP | A Note on Restricted Forms of LGG. | Ondrej Kuzelka, Jan Ramon |
| 2015 | UAI | Encoding Markov logic networks in Possibilistic Logic. | Ondrej Kuzelka, Jesse Davis, Steven Schockaert |
| 2013 | ILP | Predicting Top-k Trends on Twitter using Graphlets and Time Features. | Gustav Sourek, Ondrej Kuzelka, Filip Zelezn |
| 2012 | ILP | Bounded Least General Generalization. | Ondrej Kuzelka, Andrea Szabov, Filip Zelezn |
| 2012 | ICTAI | Relational Learning with Polynomials. | Ondrej Kuzelka, Andrea Szabov, Filip Zelezn |
| 2010 | AAAI | Formulating Template Consistency in Inductive Logic Programming as a Constraint Satisfaction Problem. | Roman Bartk, Ondrej Kuzelka, Filip Zelezn |
| 2010 | FlAIRS | Using Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming. | Roman Bartk, Ondrej Kuzelka, Filip Zelezn |
| 2010 | ILP | Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples. | Ondrej Kuzelka, Filip Zelezn |
| 2010 | SOFSEM | Taming the Complexity of Inductive Logic Programming. | Filip Zelezn, Ondrej Kuzelka |
| 2009 | ICML | Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties. | Ondrej Kuzelka, Filip Zelezn |
| 2008 | ICML | Fast estimation of first-order clause coverage through randomization and maximum likelihood. | Ondrej Kuzelka, Filip Zelezn |